Intelliswift
Job Title:
ML Talent Partner & Researcher Location:
San Jose, CA Hybrid (3 days in-office) Duration:
6 months Contract Type:
W2 only Pay Rate:
$63.38/Hour
Role Mandate:
We are seeking a highly skilled Talent Researcher/Talent Partner with deep expertise in sourcing and recruiting top AI/ML talent. This role combines advanced research sourcing techniques with full cycle recruiting capabilities to attract and secure world-class technical talent in a competitive landscape.
Responsibilities: Talent Research & Sourcing; AI/ML Focus
Identify, engage, and build pipelines of top-tier AI/ML talent. Leverage creative sourcing techniques using LinkedIn Recruiter, GitHub, Kaggle, Boolean search, research publications, and academic networks. Conduct market research and competitor analysis to understand talent availability, compensation trends, and skills in demand. Develop innovative strategies to engage passive candidates in the AI/ML space. Provide data-driven insights and market intelligence to inform hiring decisions and guide recruitment strategy.
Talent Advisory & Full-Cycle Recruiting
Partner with hiring managers to define hiring strategies aligned with business priorities in AI/ML and applied sciences. Drive end-to-end recruitment, including pipelining, interviews, stakeholder management, and offer negotiation. Support the hiring process with agility; interview coordination, debriefs, and event planning for candidate engagement.
Required Skills:
5+ years of recruiting experience, including 3+ years as a Talent Partner/Advisor or equivalent in technology-driven roles. Demonstrated experience sourcing and recruiting core AI/ML talent, including applied scientists, ML engineers, computer vision experts, and related applied research roles. Strong sourcing skills with proficiency in LinkedIn Recruiter, Boolean search, GitHub, Kaggle, and academic networks. Deep understanding of applied science, modeling, computer vision, and machine learning domains. Exceptional communication and stakeholder management skills. Familiarity with ATS tools such as Phenom, Workday, or similar. Collaborative, agile mindset with ability to support peers and drive hiring priorities.
ML Talent Partner & Researcher Location:
San Jose, CA Hybrid (3 days in-office) Duration:
6 months Contract Type:
W2 only Pay Rate:
$63.38/Hour
Role Mandate:
We are seeking a highly skilled Talent Researcher/Talent Partner with deep expertise in sourcing and recruiting top AI/ML talent. This role combines advanced research sourcing techniques with full cycle recruiting capabilities to attract and secure world-class technical talent in a competitive landscape.
Responsibilities: Talent Research & Sourcing; AI/ML Focus
Identify, engage, and build pipelines of top-tier AI/ML talent. Leverage creative sourcing techniques using LinkedIn Recruiter, GitHub, Kaggle, Boolean search, research publications, and academic networks. Conduct market research and competitor analysis to understand talent availability, compensation trends, and skills in demand. Develop innovative strategies to engage passive candidates in the AI/ML space. Provide data-driven insights and market intelligence to inform hiring decisions and guide recruitment strategy.
Talent Advisory & Full-Cycle Recruiting
Partner with hiring managers to define hiring strategies aligned with business priorities in AI/ML and applied sciences. Drive end-to-end recruitment, including pipelining, interviews, stakeholder management, and offer negotiation. Support the hiring process with agility; interview coordination, debriefs, and event planning for candidate engagement.
Required Skills:
5+ years of recruiting experience, including 3+ years as a Talent Partner/Advisor or equivalent in technology-driven roles. Demonstrated experience sourcing and recruiting core AI/ML talent, including applied scientists, ML engineers, computer vision experts, and related applied research roles. Strong sourcing skills with proficiency in LinkedIn Recruiter, Boolean search, GitHub, Kaggle, and academic networks. Deep understanding of applied science, modeling, computer vision, and machine learning domains. Exceptional communication and stakeholder management skills. Familiarity with ATS tools such as Phenom, Workday, or similar. Collaborative, agile mindset with ability to support peers and drive hiring priorities.